Methods and Systems for Modifying Content of an Electronic Learning System for Vision Deficient Users

ABSTRACT

A computer-implemented method for modifying one or more contents of an electronic learning system for a user impaired by a colour vision deficiency. The method includes: generating a vision profile for the user, the vision profile indicating at least a type of the colour vision deficiency, identifying, from the one or more contents, a content to be modified, the content including at least two portions formed of a first colour and a second colour, respectively, the first colour being different from the second colour but the first colour being at least partially indistinguishable from the second colour by the user due to the colour vision deficiency, identifying a content transformation to be applied to the content based on the vision profile, the content transformation including one or more adjustments of the content to accommodate the colour vision deficiency impairing the user; and applying the content transformation to the content.

TECHNICAL FIELD

The described embodiments relate to methods and systems associated withmodifying content of an electronic learning system for vision deficientusers and in particular, for users impaired by a colour visiondeficiency.

INTRODUCTION

Electronic learning (also known as “e-Learning” or “eLearning”)generally refers to education or learning where users engage ineducation related activities using computers and other computingdevices. For example, users may enroll or participate in a course orprogram of study offered by an educational institution (e.g., a college,university or grade school) through a web interface that is accessibleover the Internet. Users may receive assignments electronically,participate in group work and projects by collaborating over theInternet, and be graded based on assignments and examinations that aresubmitted, for example, using an electronic submission tool.

Electronic learning is not limited to use by educational institutions.Electronic learning may be used in other environments, such asgovernment and corporations. For example, employees at a regional branchoffice of a corporation may use electronic learning to participate in atraining course offered by another office, or even a third-partyprovider. As a result, the employees at the regional branch office canparticipate in the training course without having to travel to the siteproviding the training course. Travel time and costs can be reduced andconserved.

As electronic learning becomes more widespread, the user base increasesin diversity and so, the ability to adapt electronic learning systems toaccommodate as many types of users as possible becomes increasinglyimportant. For example, certain content, or at least a portion of thecontent, provided by electronic learning systems may not be viewable byusers impaired by a vision deficiency. As a result, those users areprevented from using the electronic learning systems to the fullestextent, or even at all.

BRIEF DESCRIPTION OF THE DRAWINGS

Several embodiments will now be described in detail with reference tothe drawings, in which:

FIG. 1 is a schematic diagram of components interacting with anelectronic learning system in accordance with some embodiments;

FIG. 2 is a block diagram of some components that may be implemented inthe electronic learning system in accordance with an example embodiment;

FIG. 3 is a flowchart diagram of an example method for modifyingcontents of the electronic learning system;

FIG. 4A is a screenshot of an example user interface for the electroniclearning system;

FIG. 4B is a screenshot of an example user profile for a user of theelectronic learning system;

FIG. 5A is a screenshot of a content of the electronic learning systemin accordance with an example embodiment;

FIG. 5B is a screenshot of a modified version of FIG. 5A in accordancewith an example embodiment;

FIG. 6A is a screenshot of another content of the electronic learningsystem in accordance with an example embodiment;

FIG. 6B is a screenshot of a modified version of FIG. 6A in accordancewith an example embodiment;

FIG. 7 is a flowchart diagram of an example method for assessing contentof the electronic learning system; and

FIG. 8 is a screenshot of another version of FIG. 5A in accordance withanother example embodiment.

The drawings, described below, are provided for purposes ofillustration, and not of limitation, of the aspects and features ofvarious examples of embodiments described herein.

DESCRIPTION OF SOME EMBODIMENTS

For simplicity and clarity of illustration, elements shown in thedrawings have not necessarily been drawn to scale. The dimensions ofsome of the elements may be exaggerated relative to other elements forclarity. It will be appreciated that for simplicity and clarity ofillustration, where considered appropriate, reference numerals may berepeated among the drawings to indicate corresponding or analogouselements or steps. In addition, numerous specific details are set forthin order to provide a thorough understanding of the exemplaryembodiments described herein. However, it will be understood by those ofordinary skill in the art that the embodiments described herein may bepracticed without these specific details. In other instances, well-knownmethods, procedures and components have not been described in detail soas not to obscure the embodiments generally described herein.Furthermore, this description is not to be considered as limiting thescope of the embodiments described herein in any way, but rather asmerely describing the implementation of various embodiments asdescribed.

The embodiments of the systems and methods described herein may beimplemented in hardware or software, or a combination of both. In somecases, embodiments may be implemented in one or more computer programsexecuting on one or more programmable computing devices comprising atleast one processor, a data storage component (including volatile memoryor non-volatile memory or other data storage elements or a combinationthereof) and at least one communication interface.

For example and without limitation, the programmable computers (referredto below as computing devices) may be a server, network appliance,embedded device, computer expansion module, a personal computer, laptop,personal data assistant, cellular telephone, smart-phone device, tabletcomputer, a wireless device or any other computing device capable ofbeing configured to carry out the methods described herein.

In some embodiments, the communication interface may be a networkcommunication interface. In embodiments in which elements are combined,the communication interface may be a software communication interface,such as those for inter-process communication (IPC). In still otherembodiments, there may be a combination of communication interfacesimplemented as hardware, software, and combination thereof.

In some embodiments, each program may be implemented in a high levelprocedural or object-oriented programming and/or scripting language tocommunicate with a computer system. However, the programs can beimplemented in assembly or machine language, if desired. In any case,the language may be a compiled or interpreted language.

Program code may be applied to input data to perform the functionsdescribed herein and to generate output information. The outputinformation is applied to one or more output devices, in known fashion.

Each program may be implemented in a high level procedural or objectoriented programming and/or scripting language, or both, to communicatewith a computer system. However, the programs may be implemented inassembly or machine language, if desired. In any case, the language maybe a compiled or interpreted language. Each such computer program may bestored on a storage media or a device (e.g. ROM, magnetic disk, opticaldisc) readable by a general or special purpose programmable computer,for configuring and operating the computer when the storage media ordevice is read by the computer to perform the procedures describedherein.

In some embodiments, the systems and methods as described herein mayalso be implemented as a non-transitory computer-readable storage mediumconfigured with a computer program, wherein the storage medium soconfigured causes a computer to operate in a specific and predefinedmanner to perform at least some of the functions as described herein.

Furthermore, the systems, processes and methods of the describedembodiments are capable of being distributed in a computer programproduct comprising a computer readable medium that bears computer usableinstructions for one or more processors. The medium may be provided invarious forms, including one or more diskettes, compact disks, tapes,chips, wireline transmissions, satellite transmissions, internettransmission or downloadings, magnetic and electronic storage media,digital and analog signals, and the like. The computer useableinstructions may also be in various forms, including compiled andnon-compiled code.

The various embodiments described herein generally relate to methods(and associated systems configured to implement the methods) formodifying one or more contents of an electronic learning system.Electronic learning is becoming more widespread and therefore, theability to adapt electronic learning systems so that they are suitablefor use by as many individuals as possible can be critical. For example,individuals impaired by a vision deficiency, such as colour blindness,can sometimes be limited in their use of, or perhaps even prevented fromusing, electronic learning systems.

Generally speaking, the content described herein includes various typesof course content, including for example user generated content as wellas other content such as readings, quizzes, examinations assignments,and so on. For instance, some examples of user generated content couldinclude HTML marked-up chat entries in an electronic learning systemmade by students and/or instructors, HTML marked-up email sent bystudents and/or instructors, and HTML marked-up discussion posts made bystudents and/or instructors.

Normal colour vision, for humans, relies on three types of cone cells inthe eye. The three types of cone cells are sensitive to three respectivespectra of light within the visible light spectrum, resulting intrichromatic colour vision. Colour blindness can involve any degree ofdeficiency in any one or more of the cone cells so that, as a result, aspecific section of the visible light spectrum cannot be perceived.Dichromatic colour vision, for example, is when only two types of conecells are functional, while monochromatic colour vision is when only onetype of cone cell is functional (e.g., mostly black and white visionconsisting of different shades of grey).

Red-blindness, or protanopia, is when the red cone cells are absent ornot functional. As noted, it is possible that the red cone cells areonly reduced in sensitivity, which can be referred to as protanomaly.Generally, individuals with red-blindness perceive the colour red to bedarker and tend to confuse black with shades of red; dark brown withdark green, dark orange and dark red; some shades of blue with someshades of red, purples and dark pinks; and mid-greens with some shadesof orange.

Green-blindness, or deuteranopia, is when the green cone cells areabsent or not functional. Again, it is possible that the green conecells are only reduced in sensitivity, which can be referred to asdeuteranomaly. Generally, individuals with green-blindness confuseshades of mid-red with shades of mid-green or mid-brown; shades ofblue-green with grey and shades of mid-pink; shades of bright green withshades of yellow; shades of pale pink with light grey; and shades oflight blue with lilac.

Blue-blindness, or tritanopia, is when the blue cone cells are absent ornot functional. Again, it is possible that the blue cone cells are onlyreduced in sensitivity, which can be referred to as tritanomaly.Generally, individuals with blue blindness confuse blue with green, andyellow with violet.

Red-blindness and green-blindness are generally more common thanblue-blindness.

Contents provided by the electronic learning systems typically involvesome colour. Colour can often help capture, and perhaps retain, aviewer's attention, and may sometimes be incorporated as part of thecontent. For example, the contents can include images, graphs and textin which colour is a significant component—a pie graph, for instance,can include sectors distinguished by different colours; various portionsof a text document can be distinguished by different colours; and imagescan include components composed of various different colours.Individuals impaired by any degree and type of colour blindness can,therefore, experience difficulties when using electronic learningsystems.

Unlike traditional learning environments, such as a classroom setting,providers of the electronic learning systems, as well as contentcreators and content publishers for the electronic learning systems, areless able to detect, or at least less able to detect within a reasonableamount of time, content users' perception of the content. In traditionallearning environments, instructors usually have the opportunity tointeract, face-to-face, with the students, and would likely have greateropportunities to detect a vision deficiency impairing the students.

Electronic learning, on the other hand, typically involves at least someself-study by the users before the users submit any work product forreview by the content creator, content creator or instructor. A courseprovided by the electronic learning system, for example, can includemultiple modules with a majority of the contents not requiring anyresponse from the user and rather, only for the user to view or read. Itis possible that only at the end of a module, or perhaps even at the endof the course, that the user submits any work product or undergoes someform of evaluation related to the course. As a result, when anindividual impaired by a vision deficiency participates in the course,some of the contents may not be suitable for the individual. That is,the individual may be unable to perceive the contents in the way thatwas intended by the content creator due to the vision deficiency. Theindividual may also not be aware of the discrepancy between how thecontents are actually shown by the electronic learning system and howthe contents are perceived by the individual. However, even if theindividual is, or becomes, aware of the discrepancy and notifies thecontent provider of the discrepancy, it may be difficult for the contentprovider to adjust or replace the contents within a reasonable amount oftime.

The electronic learning systems described herein can modify the contentsfor users impaired by a vision deficiency. In order to determine whetherany of the contents require modification, the described electroniclearning systems can generate a vision profile for each of the users.The vision profile can indicate whether or not a user is impaired by avision deficiency. In the case that the vision profile indicates thatthe user is impaired by a vision deficiency, the described electroniclearning systems can identify and perform the content transformationnecessary for adjusting the content to accommodate the visiondeficiency.

The described electronic learning systems may also facilitate creationof the contents by assessing the contents and indicating to the contentcreator, at the time of creation, that certain contents may bedeficient. For an individual impaired by a colour vision deficiency, acontent may be deficient if the content contains portions formed ofcolours that would be at least partially indistinguishable from eachother due to the colour vision deficiency. The content creator may thenadjust or replace the content accordingly.

Referring now to FIG. 1, illustrated therein is a schematic diagram 10of components interacting with an electronic learning system 30 forproviding electronic learning according to some embodiments.

As shown in the schematic diagram 10, one or more users 12, 14 mayaccess the electronic learning system 30 to participate in, create, andconsume electronic learning services, including educational content suchas courses. In some cases, the electronic learning system 30 may be partof (or associated with) a traditional “bricks and mortar” educationalinstitution (e.g. a grade school, university or college), another entitythat provides educational services (e.g. an online university, a companythat specializes in offering training courses, an organization that hasa training department, etc.), or may be an independent service provider(e.g. for providing individual electronic learning).

It should be understood that a course is not limited to formal coursesoffered by formal educational institutions. The course may include anyform of learning instruction offered by an entity of any type. Forexample, the course may be a training seminar at a company for a groupof employees or a professional certification program (e.g. ProjectManagement Professional™ (PMP), Certified Management Accountants (CMA),etc.) with a number of intended participants.

In some embodiments, one or more educational groups 16 can be defined toinclude one or more users 12, 14. For example, as shown in FIG. 1, theusers 12, 14 may be grouped together in the educational group 16. Theeducational group 16 can be associated with a particular course (e.g.History 101 or French 254, etc.), for example. The educational group 16can include different types of users. A first user 12 can be responsiblefor organizing and/or teaching the course (e.g. developing lectures,preparing assignments, creating educational content, etc.), such as aninstructor or a course moderator. The other users 14 can be consumers ofthe course content, such as students.

In some examples, the users 12, 14 may be associated with more than oneeducational group 16 (e.g. some users 14 may be enrolled in more thanone course, another example user 12 may be a student enrolled in onecourse and an instructor responsible for teaching another course, afurther example user 12 may be responsible for teaching several courses,and so on).

In some examples, educational sub-groups 18 may also be formed. Forexample, the users 14 shown in FIG. 1 form an educational sub-group 18.The educational sub-group 18 may be formed in relation to a particularproject or assignment (e.g. educational sub-group 18 may be a lab group)or based on other criteria. In some embodiments, due to the nature ofelectronic learning, the users 14 in a particular educational sub-group18 may not need to meet in person, but may collaborate together usingvarious tools provided by the electronic learning system 30.

In some embodiments, other educational groups 16 and educationalsub-groups 18 could include users 14 that share common interests (e.g.interests in a particular sport), that participate in common activities(e.g. users that are members of a choir or a club), and/or have similarattributes (e.g. users that are male, users under twenty-one years ofage, etc.).

Communication between the users 12, 14 and the electronic learningsystem 30 can occur either directly or indirectly using any one or moresuitable computing devices. For example, the user 12 may use a computingdevice 20 having one or more device processors such as a desktopcomputer that has at least one input device (e.g. a keyboard and amouse) and at least one output device (e.g. a display screen andspeakers).

The computing device 20 can generally be any suitable device forfacilitating communication between the users 12, 14 and the electroniclearning system 30. For example, the computing device 20 could bewirelessly coupled to an access point 22 (e.g. a wireless router, acellular communications tower, etc.), such as a laptop 20 a, awirelessly enabled personal data assistant (PDA) or smart phone 20 b, atablet computer 20 d, or a game console 20 e. The computing device 20could be coupled to the access point 22 over a wired connection 23, suchas a computer terminal 20 c.

The computing devices 20 may communicate with the electronic learningsystem 30 via any suitable communication channels.

The computing devices 20 may be any networked device operable to connectto the network 28. A networked device is a device capable ofcommunicating with other devices through a network, such as the network28. A network device may couple to the network 28 through a wired orwireless connection.

As noted, these computing devices may include at least a processor andmemory, and may be an electronic tablet device, a personal computer,workstation, server, portable computer, mobile device, personal digitalassistant, laptop, smart phone, WAP phone, an interactive television,video display terminals, gaming consoles, and portable electronicdevices or any combination of these. These computing devices may behandheld and/or wearable by the user.

In some embodiments, these computing devices may be a laptop 20 a, or asmartphone device 20 b equipped with a network adapter for connecting tothe Internet. In some embodiments, the connection request initiated fromthe computing devices 20 a, 20 b may be initiated from a web browser anddirected at the browser-based communications application on theelectronic learning system 30.

For example, the computing devices 20 may communicate with theelectronic learning system 30 via the network 28. The network 28 mayinclude a local area network (LAN) (e.g., an intranet) and/or anexternal network (e.g., the Internet). For example, the computingdevices 20 may access the network 28 by using a browser applicationprovided on the computing device 20 to access one or more web pagespresented over the Internet via a data connection 27.

The network 28 may be any network capable of carrying data, includingthe Internet, Ethernet, plain old telephone service (POTS) line, publicswitch telephone network (PSTN), integrated services digital network(ISDN), digital subscriber line (DSL), coaxial cable, fiber optics,satellite, mobile, wireless (e.g. Wi-Fi, WiMAX), SS7 signaling network,fixed line, local area network, wide area network, and others, includingany combination of these, capable of interfacing with, and enablingcommunication between the computing devices 20 and the electroniclearning system 30, for example.

In some examples, the electronic learning system 30 may authenticate anidentity of one or more of the users 12, 14 prior to granting the user12, 14 access to the electronic learning system 30. For example, theelectronic learning system 30 may require the users 12, 14 to provideidentifying information (e.g., a login name and/or a password) in orderto gain access to the electronic learning system 30.

In some examples, the electronic learning system 30 may allow certainusers 12, 14, such as guest users, access to the electronic learningsystem 30 without requiring authentication information to be provided bythose guest users. Such guest users may be provided with limited access,such as the ability to review one or more components of the course todecide whether they would like to participate in the course but withoutthe ability to post comments or upload electronic files.

In some embodiments, the electronic learning system 30 may communicatewith the access point 22 via a data connection 25 established over theLAN. Alternatively, the electronic learning system 30 may communicatewith the access point 22 via the Internet or another external datacommunications network. For example, one user 14 may use the laptop 20 ato browse to a webpage (e.g. a course page) that displays elements ofthe electronic learning system 30.

The electronic learning system 30 can include one or more components forproviding electronic learning services. It will be understood that insome embodiments, each of the one or more components may be combinedinto fewer number of components or may be separated into furthercomponents. Furthermore, the one or more components in the electroniclearning system 30 may be implemented in software or hardware, or acombination of software and hardware.

For example, the electronic learning system 30 can include one or moreprocessing components, such as computing servers 32. Each computingserver 32 can include one or more processor. The processors provided atthe computing servers 32 can be referred to as “system processors” whileprocessors provided at computing devices 20 can be referred to as“device processors”. The computing servers 32 may be a computing device20 (e.g. a laptop or personal computer).

It will be understood that although two computing servers 32 are shownin FIG. 1, one or more than two computing servers 32 may be provided.The computing servers 32 may be located locally together, or distributedover a wide geographic area and connected via the network 28.

The system processors may be configured to control the operation of theelectronic learning system 30. The system processors can initiate andmanage the operations of each of the other components in the electroniclearning system 30. The system processor may also determine, based onreceived data, stored data and/or user preferences, how the electroniclearning system 30 may generally operate.

The system processor may be any suitable processors, controllers ordigital signal processors that can provide sufficient processing powerdepending on the configuration, purposes and requirements of theelectronic learning system 30. In some embodiments, the system processorcan include more than one processor with each processor being configuredto perform different dedicated tasks.

In some embodiments, the computing servers 32 can transmit data (e.g.electronic files such as web pages) over the network 28 to the computingdevices 20. The data may include electronic files, such as webpages withcourse information, associated with the electronic learning system 30.Once the data is received at the computing devices 20, the deviceprocessors can operate to display the received data.

The electronic learning system 30 may also include one or more datastorage components 34 that are in electronic communication with thecomputing servers 32. The data storage components 34 can include RAM,ROM, one or more hard drives, one or more flash drives or some othersuitable data storage elements such as disk drives, etc. The datastorage components 34 may include one or more databases, such as arelational database (e.g., a SQL database), for example.

The data storage components 34 can store various data associated withthe operation of the electronic learning system 30. For example, coursedata 35, such as data related to a course's framework, educationalcontent, and/or records of assessments, may be stored at the datastorage components 34. The data storage components 34 may also storeuser data, which includes information associated with the users 12, 14.The user data may include a user profile for each user 12, 14, forexample. The user profile may include personal information (e.g., name,gender, age, birthdate, contact information, interests, hobbies, etc.),authentication information to the electronic learning system 30 (e.g.,login identifier and password) and educational information (e.g., whichcourses that user is enrolled in, the user type, course contentpreferences, etc.).

The data storage components 34 can store authorization criteria thatdefine the actions that may be taken by certain users 12, 14 withrespect to the various educational contents provided by the electroniclearning system 30. The authorization criteria can define differentsecurity levels for different user types. For example, there can be asecurity level for an instructing user who is responsible for developingan educational course, teaching it, and assessing work product from thestudent users for that course. The security level for those instructingusers, therefore, can include, at least, full editing permissions toassociated course content and access to various components forevaluating the students in the relevant courses.

In some embodiments, some of the authorization criteria may bepre-defined. For example, the authorization criteria can be defined byadministrators so that the authorization criteria are consistent for theelectronic learning system 30, as a whole. In some further embodiments,the electronic learning system 30 may allow certain users, such asinstructors, to vary the pre-defined authorization criteria for certaincourse contents.

The electronic learning system 30 can also include one or more backupservers 31. The backup server can store a duplicate of some or all ofthe data 35 stored on the data storage components 34. The backup server31 may be desirable for disaster recovery (e.g. to prevent data loss inthe case of an event such as a fire, flooding, or theft). It should beunderstood that although only one backup server 31 is shown in FIG. 1,one or more backup servers 31 may be provided in the electronic learningsystem 30. The one or more backup servers 31 can also be provided at thesame geographical location as the electronic learning system 30, or oneor more different geographical locations.

The electronic learning system 30 can include other components forproviding the electronic learning services. For example, the electroniclearning system 30 can include a management component that allows users12, 14 to add and/or drop courses and a communication component thatenables communication between the users 12, 14 (e.g., a chat software,etc.). The communication component may also enable the electroniclearning system 30 to benefit from tools provided by third-partyvendors. Other example components will be described with reference toFIG. 2.

Referring now to FIG. 2, which is a block diagram 200 of some componentsthat may be implemented in the electronic learning system 30 accordingto some embodiments. In the example of FIG. 2, the various illustratedcomponents are provided at one of the computing servers 32.

As shown in FIG. 2, the computing server 32 may include a systemprocessor 210, an interface component 220, a local storage component 230and a transformation component 240. Each of the system processor 210,the interface component 220, the local storage component 230 and thetransformation component 240 can be in electronic communication with oneanother. It should be noted that in alternative embodiments, the systemprocessor 210, the interface component 220, the local storage component230 and the transformation component 240 may be combined or may beseparated into further components. Furthermore, the system processor210, the interface component 220, the local storage component 230 andthe transformation component 240 may be implemented using software,hardware or a combination of both software and hardware.

Generally, the system processor 210 controls the operation of thecomputing server 32 and, as a result, various operations of theelectronic learning system 30. For example, the system processor 210 mayinitiate the transformation component 240 to identify a contenttransformation to be applied to the content(s) and to apply the contenttransformation to the respective content(s) provided by the electroniclearning system 30 in accordance with the methods described herein. Thesystem processor 210 may also initiate the transformation component 240to assess the contents to determine whether any of the content(s) aredeficient and to advise the content creator accordingly.

The interface component 220 may be any interface that enables thecomputing server 32 to communicate with the other computing servers 32,backup servers 31 and data storage components 34 within the electroniclearning system 30. The interface component 220 may also include anyinterface that enables the computing server 32 to communicate withthird-party systems. In some embodiments, the interface component 220can include at least one of a serial port, a parallel port or a USBport. The interface component 220 may also include at least one of anInternet, Local Area Network (LAN), Ethernet, Firewire, modem or digitalsubscriber line connection. Various combinations of these elements maybe incorporated within the interface component 220.

In some embodiments, the interface component 220 may receive input fromthe computing devices 20 via various input components, such as a mouse,a keyboard, a touch screen, a thumbwheel, a track-pad, a track-ball, acard-reader, voice recognition software and the like depending on therequirements and implementation of the electronic learning system 30.

The local storage component 230 may be provided at the computing server32 for temporary storage of data associated with various operations ofthe system processor 210. The local storage component 230 may receivedata from and/or transmit data to the data storage components 34.

The transformation component 240 can include the software and dataassociated with the various methods for modifying and assessing contentfor an electronic learning system 30 as described herein. Exampleembodiments will now be described with reference to FIGS. 3 to 6B.

Referring now to FIG. 3, a flowchart diagram illustrating an examplemethod 300 for modifying contents of the electronic learning system 30is shown. To illustrate the method 300, reference will be madesimultaneously to FIGS. 4A to 6B.

At 310, the system processor 210 generates a vision profile for theuser.

Generally, as will be described with reference to FIG. 4B, the visionprofile can indicate, at least, a vision deficiency that may beimpairing the user. For example, the vision profile may indicate a typeand/or a degree of colour vision deficiency impairing the user, such asred-blindness or a combination of red-blindness and green-blindness. Thedegree of vision deficiency may be selected from one of no deficiency,moderately deficient, strongly deficient and absolutely deficient.

The system processor 210 can generate the vision profile byadministering a vision test to the user and/or by obtaining inputs fromthe user associated with his or her vision.

FIG. 4A is a screenshot 400 of an example user interface 404 for theelectronic learning system 30. The user interface 404 can be providedvia a browser application, such as 402.

As shown, the user interface 404 is an example main screen for a user of“City College's” e-learning system. The user interface 404 includes acurrent semester component 410 (e.g., “Fall” semester component), anacademic information component 420, a tools component 430 and a userprofile component 440. It will be understood that the user interface 404is merely an example and that other components may similarly be providedor replace the components shown.

The current semester component 410 can list courses for which the useris registered for that semester. Each of the listed courses may alsoinclude a link selectable to provide further details on the respectivecourses.

The academic information component 420 can include selectable links todata associated with the user's course schedule and grades, for example.Other information relevant to the user's education may be provided.

The tools component 430 can include selectable links to various toolsand components. Example tools may include chat software or othermessaging components. A settings tool may also be provided in the toolscomponent 430 for varying certain aspects of the electronic learningsystem for that user.

The user profile component 440 can include selectable links to providedata associated with the user or to collect data from the user. Forexample, a personal information link 442 can be selected to display auser profile interface 454, such as the example shown in FIG. 4B. Anextracurricular activities link 444 can display various informationrelated to clubs and teams that the user is involved in.

A vision test link 446 can be selected to provide one or more visiontests for collecting data from the user for generating a vision profilefor the user. In some embodiments, the electronic learning system 30 mayadminister one or more vision tests automatically when the userinitially logs into the system 30.

Various vision tests can be administered to the user via a display of acomputing device 20. Example vision tests can include Ishihara tests,Farnsworth Lantern tests, versions of the Ishihara tests and versions ofthe Farnsworth Lantern tests (e.g., Farnsworth-Munsell 100 hue test),and other related vision perception tests. As is generally known in theart, the Ishihara test and the Farnsworth Lantern test are examplecolour perception tests for red-blindness and green-blindness.

When generating a vision profile for the user, the electronic learningsystem 30 may administer multiple different vision tests for each user.The application of multiple different vision tests can help develop amore detailed, and possibly more accurate, vision profile for the user.Based substantially on the results from the various vision tests, theelectronic learning system 30 can create the vision profile.

For example, the electronic learning system 30 can determine from theresults of an Ishihara test that the user is impaired by relativelystrong red-blindness and less than moderate green-blindness, and theelectronic learning system 30 can also determine from the results of aFarnsworth Lantern test that the user is impaired by strongred-blindness and moderate green-blindness. The electronic learningsystem 30 can generate a vision profile for the user by considering theresults from both tests. Certain test results may be more reliable forparticular types of vision deficiencies, and therefore, the electroniclearning system 30 may apply various weights to the test results whengenerating the vision profile. An example vision profile is shown inFIG. 4B.

The electronic learning system 30 may also store the vision profile inthe local storage component 230 and/or the data storage components 34 inassociation with the user's profile.

Referring now to FIG. 4B, which is a screenshot 450 of an example userprofile interface 454. The user profile interface 454 can includevarious personal information associated with the user, such as a profileimage 462, a first name field 464, a last name field 466, a birthdatefield 468 and contact information 470 (e.g., an electronic mail addressfield 472 and a home address field 474). It will be understood thatother relevant personal information may similarly be provided in theuser profile interface 454.

As shown in the user profile interface 454 for the user, “John Smith”, avision profile 480 is also provided. Continuing with the above example,the vision profile 480 can be generated based on the results from theIshihara test and the Farnsworth Lantern test administered by theelectronic learning system 30. In some embodiments, the electroniclearning system 30 may also consider vision information provided by theuser apart from the vision tests when generating the vision profile 480.From the vision profile 480, the user “John Smith” is impaired by colourvision deficiency, namely a relatively strong degree of red-blindness(as shown from a red-blindness indicator 482) and a relatively moderatedegree of green-blindness (as shown from a green-blindness indicator484). The severity of the red-blindness and green-blindness is a blendof the results from the Ishihara test and the Farnsworth Lantern test.The user “John Smith” does not appear to be impaired by blue-blindness(as shown from a blue-blindness indicator 486).

At 320, the system processor 210 identifies, based on the vision profile480, a content transformation to be applied to a content.

The content transformation can include adjustments to the content inorder to accommodate the vision deficiency impairing the user. Forexample, for the user “John Smith”, the system processor 210 canidentify the content transformation needed to adjust the relevantcontents to accommodate the relatively strong red-blindness andrelatively moderate green-blindness.

When identifying the content transformation, the system processor 210may also identify contents requiring modification based on the visionprofile 480. It may be possible that some contents provided by theelectronic learning system 30 may not require modification since theymay be viewable by the user despite being impaired by the visiondeficiency. For example, contents with only text in one colour unlikelyrequire modification. As a result, processing resources at theelectronic learning system 30 can be conserved.

When the vision profile 480 includes a colour vision deficiency, thesystem processor 210 can identify the content to be modified based onthe presence of at least two colours that are at least partiallyindistinguishable by the user due to the colour vision deficiency. Anexample content is shown in FIG. 5A.

FIG. 5A is a screenshot 500A of an example content of the electroniclearning system 30. The content in FIG. 5A is a graph 504A showingcourse statistics for a Fall semester of the Calculus I course. Thegraph 504A is a column graph in which one column depicts a class averageand another column depicts the user's marks. The two columns can bedistinguished using two different colours (as shown in the legend 510A).In this example, the column associated with the class average is in red(as indicated at 512A in the legend 510A) and the column associated withthe user's marks is in green (as indicated at 514A in the legend 510A).

For the graph 504A, the system processor 210 can determine that at leasttwo portions are formed of a first colour (red) and a second colour(green). In some embodiments, the two portions may be neighbouringportions with at least some of the perimeter of one portion being incontact, or at least in very close proximity, with a perimeter of theother portion. Based on the vision profile 480 for “John Smith”, thesystem processor 210 can determine that the first colour (red) is likelyto be at least partially indistinguishable from the second colour(green) since the vision profile 480 indicates that “John Smith” isaffected by varying degrees of red-blindness and green-blindness.

As described, individuals impaired by red-blindness and green-blindnesshave absent or non-functional red cone cells and green cone cells,respectively. The portions of the visible light spectrum for which thered cone cell and the green cone cell are responsible overlap, andtherefore, individuals affected by red-blindness and green-blindnessoften perceive colours similarly. In particular, individuals impaired byred-blindness and green-blindness will have difficulty distinguishingbetween red and green.

Due to the green and red columns, the system processor 210 can,therefore, determine that the graph 504A is a content for which contenttransformation is to be applied based on the vision profile 480 of theuser “John Smith”.

The content transformation can vary depending on the vision profile 480.In particular, the severity and the type of the vision deficiency canaffect the content transformation to be applied to the content.

In some embodiments, the system processor 210 can identify the contenttransformation to include replacing the colour(s) with anothercolour(s). For example, a content transformation for an image withneighbouring portions coloured with different colours that would be atleast partially indistinguishable, or perhaps even be perceived as thesame colour, by the user can include replacing the colour of one of theneighbouring portions with another colour.

An example colour replacement method can include an edge detectionalgorithm followed by a flood fill algorithm. It will be understood thatother colour replacement methods may similarly be applied.Alternatively, the system processor 210 can adjust the cascading stylesheets (CSS) associated with the content.

In respect of the graph 504A in FIG. 5A, the system processor 210 canidentify the content transformation to include a replacement of thecolour “red” (representing the class average) with a colour more easilydistinguishable from the colour “green”, such as white perhaps.Alternatively, the system processor 210 can replace green with a colourthat is more easily distinguishable from red.

To identify the replacement colour, the system processor 210 mayidentify a set of colours that can be distinguished by the user based onthe vision profile 480. For example, for the user “John Smith”, thesystem processor 210 can determine that since “John Smith” is impairedby varying degrees of red-blindness and green-blindness, the set ofreplacement colours can include colours outside of the red and greenregions of the visible light spectrum. The system processor 210 can thenreplace the indistinguishable colour with one of the colours in the setof replacement colours.

For less severe vision deficiencies, the system processor 210 mayidentify content transformation to only include a variation of acontrast of the colour instead of a complete colour replacement. Forexample, the system processor 210 may vary a portion coloured with lightyellow to bright yellow.

In some embodiments, the system processor 210 can identify the contenttransformation to include replacement of the colours with patterns, oreven modification of the content itself. These types of contenttransformation can be applied for users impaired by very strong visiondeficiencies to absolute deficiencies, such as those affected bymonochromatic colour vision. An example application of the contenttransformation involving a replacement of a colour with a pattern willbe described with reference to FIG. 5B, and an example application ofthe content transformation involving a modification of the content willbe described with reference to FIGS. 6A and 6B.

FIG. 5B is a screenshot 500B of a graph 504B modified in accordance withan example embodiment based on the column graph 504A of FIG. 5A. Incontrast to the graph 504A, the two columns of the graph 504B are nowdistinguished using two different patterns (as shown in the legend510B). The column associated with the class average is in a firstpattern (as shown at 512B in the legend 510B) and the column associatedwith the user's marks is in a second pattern (as shown at 514B in thelegend 510B). It will be understood that the patterns can include anyvariations of dots, lines, etc., that do not involve colours fordistinguishing between the different portions of the image. Similar tothe example colour replacement method, the pattern replacement methodcan include an edge detection algorithm followed by replacement of thedetected portions with a respective pattern. It will be understood thatother pattern replacement methods may similarly be applied.

Referring now to FIGS. 6A and 6B, which are screenshots 600A and 600B,respectively, of another example content of the electronic learningsystem 30.

The content in FIG. 6A is an exam question 604A in a midterm for thecourse, Basic French. The exam question 604A includes an image 610A anda textbox 620 for receiving a response from the user in respect of theimage 610A. The image 610A depicts scenery with the sun in differentshades of orange and yellow, clouds in blue, an apple tree with greenleaves and red apples, and a house with a brown door. Similar to thegraph 504A in FIG. 5A, the system processor 210 can determine from thevision profile 480 that the user “John Smith” would also havedifficulties identifying the colours of the various objects in the image610A due to his colour vision deficiency. To accommodate the visiondeficiency, the system processor 210 can, as described, vary the coloursin the image 610A. However, due to the importance of the exam question604A and the relevance of the image 610A on how the user will respond tothe exam question 604A, the system processor 210 may instead suggest tothe content provider that the image 610A should be modified (or replacedentirely) to ensure that the user “John Smith” can perceive the contentin accordance with the content provider's intention.

FIG. 6B shows a modified exam question 604B in which the image 610A ofFIG. 6A is now replaced with a text description 610B that generallydescribes the image 610A. Since the exam question 604A is to evaluatethe user's French vocabulary, the modified exam question 604B with thetext description 610B can likely evaluate the user's vocabulary in asimilar way as the image 610A.

The system processor 210 may also identify the content transformationbased on other factors, such as user preferences and/or predefinedsettings. Certain types of content transformation may be identified bythe content provider as being preferred in some situations. For example,the predefined settings for a vision profile 480 with strong visiondeficiency may involve an aggressive recolouration or patternreplacement for critical contents, such contents used in evaluating auser's knowledge of the course materials. Some users may also indicatecertain preferred replacement colours or patterns. It will be understoodthat other user preferences and settings may similarly be applied.

At 330, the system processor 210 applies the content transformation tothe content.

Generally, the system processor 210 applies the content transformationto the content before the content is delivered to the browserapplication 402 (or before it reaches an SMTP server to be sent viaemail) and is accessed by the user. Emails, chat entries, discussionposts entered by students or instructors may be transformed immediately,in an ad-hoc manner.

The system processor 210 may prioritize when certain contents are to betransformed based on various factors, such as the purpose of the content(e.g., whether the content is purely for decoration or for providinginformation), an expected access date of the content, and an expectedlength of time required for transforming the content. It is possiblethat the system processor 210 may segment the transformation of thecontents of a course over time. That is, the system processor 210 cantransform the portions of the course that are expected to be accessedfirst, and continue to transform the other portions over time.

The described electronic learning system 30 may also facilitate creationof the content.

When content creators first develop content for the electronic learningsystem 30, it may be helpful to identify, upfront, which content may beproblematic for users impaired by different vision deficiencies. Thiscan increase the content creator's awareness of how different content isperceived as a result of vision deficiencies and how certain designs ofthe content should be avoided, if possible.

Referring now to FIG. 7, which is a flowchart diagram illustrating anexample method 700 for assessing content for the electronic learningsystem 30. To illustrate the method 700, reference will be madesimultaneously to FIGS. 5A and 8. FIG. 8 is a screenshot 800 of a graph804, which is another version of the graph 504A of FIG. 5A.

At 710, the system processor 210 receives content data from a contentcreator for generating content for the electronic learning system 30.

The content data can include any form of data information that can beused to generate the content to be provided by the electronic learningsystem 30. The content can be course content to be provided to a groupof students, such as the educational group 16. Example content data caninclude images, text information, course statistics, course information,course roster, and other relevant information.

At 720, the system processor 210 determines whether the content isdeficient.

The content can be considered deficient when the system processor 210identifies at least two portions of the content are formed of twocolours, respectively, that are at least partially indistinguishable byan individual impaired by a colour vision deficiency. Example methodsfor identifying the portions of the content with colours that are atleast partially indistinguishable due to a vision deficiency aredescribed above with reference to 320 of FIG. 3.

The system processor 210 may, in some embodiments, determine whether anystudent in the educational group 16 is impaired by a colour visiondeficiency and determine whether the content is deficient based on thecolour vision deficiency of any of those students. The vision profile480 for each student may be previously stored in the local storagecomponent 230 or the data storage components 34, and available forretrieval by the system processor 210.

At 730, in response to determining the content is deficient, the systemprocessor 210 advises the content creator of the deficient content.

Continuing with reference to the example shown in FIG. 5A, as described,the system processor 210 can determine, for users impaired by varyingdegrees of red-blindness and green-blindness, such as the user “JohnSmith”, that the colour (red) representing the class average is likelyat least partially indistinguishable from the colour (green)representing “John Smith's” marks. When the graph 504A was beinggenerated, the system processor 210 can detect the problem caused by thecolours green and red, and advise the content creator of the deficientcontent.

When advising the content creator of the deficient content, the systemprocessor 210 may provide a version of the graph 504A as would beperceived by an individual impaired by a vision deficiency, or versionsof the graph 504A as would be perceived by individuals impaired byvarious different vision deficiencies. The modified graph 804 in FIG. 8illustrates how the graph 504A may be perceived by the user “John Smith”who is impaired by varying degrees of red-blindness and green-blindness.As shown in FIG. 8, “John Smith” is unlikely able to distinguish betweenthe red and green columns. The modified graph 804 also includes an alert820 explaining the modified graph 804. It will be understood that FIG. 8is merely an example and that other configurations and designs maysimilarly be provided.

In some embodiments, the system processor 210 may, in response todetecting a deficient content, offer replacement content for thedeficient content. The replacement content may be a version of thedeficient content with the indistinguishable colours enhanced, replacedwith distinguishable colours, or replaced with patterns. The replacementcontent may alternatively be an alternative content that the systemprocessor 210 determines to be analogous to the deficient content.

Otherwise, the system processor 210 may indicate, at 740, that thecontent is not deficient.

The embodiments herein been described here by way of example only.Various modification and variations may be made to these exampleembodiments. Also, in the various user interfaces illustrated in thefigures, it will be understood that the illustrated user interface textand controls are provided as examples only and are not meant to belimiting. Other suitable user interface elements may be possible.

1) A computer-implemented method for modifying one or more contents ofan electronic learning system for a user impaired by a colour visiondeficiency, the method comprising: generating a vision profile for theuser, the vision profile indicating at least a type of the colour visiondeficiency; identifying, from the one or more contents, a content to bemodified, the content including at least two portions formed of a firstcolour and a second colour, respectively, the first colour beingdifferent from the second colour but the first colour being at leastpartially indistinguishable from the second colour by the user due tothe colour vision deficiency; identifying a content transformation to beapplied to the content based on the vision profile, the contenttransformation including one or more adjustments of the content toaccommodate the colour vision deficiency impairing the user; andapplying the content transformation to the content. 2) The method ofclaim 1, wherein identifying the content transformation to be applied tothe content based on the vision profile comprises: determining, from thevision profile, a severity level of the colour vision deficiency; andidentifying the one or more adjustments based on the severity level. 3)The method of claim 1, wherein the one or more adjustments comprises oneof (i) changing the first colour to a different colour, (ii) replacingthe first colour with a pattern, and (iii) modifying the content. 4) Asystem for modifying one or more electronic contents for a user impairedby a colour vision deficiency, the one or more electronic contents beingprovided by an electronic learning system, the system comprising aprocessor configured to: generate a vision profile for the user, thevision profile indicating at least a type of the colour visiondeficiency; identify, from the one or more contents, a content to bemodified, the content including at least two portions formed of a firstcolour and a second colour, respectively, the first colour beingdifferent from the second colour but the first colour being at leastpartially indistinguishable from the second colour by the user due tothe colour vision deficiency; identify a content transformation to beapplied to the content based on the vision profile, the contenttransformation including one or more adjustments of the content toaccommodate the colour vision deficiency impairing the user; and applythe content transformation to the content. 5) The system of claim 4,wherein the processor is configured to: determine, from the visionprofile, a severity level of the colour vision deficiency; and identifythe one or more adjustments based on the severity level. 6) The systemof claim 4, wherein the one or more adjustments comprises one of (i)changing the first colour to a different colour, (ii) replacing thefirst colour with a pattern, and (iii) modifying the content. 7) Acomputer-implemented method for modifying one or more contents of anelectronic learning system for a user, the method comprising: generatinga vision profile for the user, the vision profile indicating at least avision deficiency impairing the user; identifying a contenttransformation to be applied to a content of the one or more contentsbased on the vision profile, the content transformation including one ormore adjustments of the content to accommodate the vision deficiencyimpairing the user; and applying the content transformation to thecontent. 8) The method of claim 7, wherein generating the vision profilefor the user comprises: providing, via a display, a vision test to theuser; and creating the vision profile based substantially on results ofthe vision test. 9) The method of claim 8, wherein the vision testcomprises at least one or more of a version of an Ishihara test and aversion of a Farnsworth Lantern test. 10) The method of claim 7, whereinidentifying the content transformation to be applied to the content ofthe one or more contents based on the vision profile comprises:determining, from the vision profile, the vision deficiency includes acolour vision deficiency; and in response to determining the visiondeficiency includes the colour vision deficiency, indicating the contenttransformation includes one of (i) changing at least one colour of thecontent to a different colour, (ii) replacing the at least one colour ofthe content with a pattern, and (iii) modifying the content. 11) Themethod of claim 10, further comprises: identifying, from the one or morecontents, the content to be modified, the content including twoneighbouring portions, each portion of the two neighbouring portionsbeing associated with a respective first and second colour, the firstcolour being different from the second colour but the first colour beingat least partially indistinguishable from the second colour by the userdue to the vision deficiency. 12) The method of claim 11 furthercomprises: identifying a set of colours distinguishable by the userdespite the vision deficiency; and changing the first colour to a colourfrom the set of colours, the colour being different from the secondcolour. 13) The method of claim 11 further comprises replacing the firstcolour with a pattern. 14) The method of claim 10 further comprises:determining, from the vision profile, a severity level of the visiondeficiency. 15) The method of claim 14, wherein the severity level isselected from one of slightly deficient, moderately deficient, stronglydeficient and absolutely deficient. 16) The method of claim 15, furthercomprises: in response to determining the severity level is absolutelydeficient, indicating the content transformation includes replacing atleast one colour of the content with a pattern. 17)-36) (canceled)